Intramolecular dynamics play an essential role in the folding and function of biomolecules and, increasingly, in the operation of many biomimetic technologies. Thus motivated we have employed both experiment and simulation to characterize the end-to-end collision dynamics of unstructured, single-stranded DNAs ranging from 6 to 26 bases. We find that, because of the size and flexibility of the optical reporters employed experimentally, end-to-end collision dynamics exhibit little length dependence at length scales <11 bases. For longer constructs, however, the end-to-end collision rate exhibits a power-law relationship to polymer length with an exponent of -3.49 +/- 0.13. This represents a significantly stronger length dependence than observed experimentally for unstructured polypeptides or predicted by polymer scaling arguments. Simulations indicate, however, that the larger exponent stems from electrostatic effects that become important over the rather short length scale of these highly charged polymers. Finally, we have found that the end-to-end collision rate also depends linearly on solvent viscosity, with an experimentally significant, nonzero intercept (the extrapolated rate at zero viscosity) that is independent of chain length--n observation that sheds new light on the origins of the "internal friction" observed in the dynamics of many polymer systems.
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http://dx.doi.org/10.1016/j.bpj.2009.04.036 | DOI Listing |
Sensors (Basel)
December 2024
Ubicom Laboratory, Department of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan 44610, Republic of Korea.
The proposed protocol features reliable and fast image transmission while periodically transmitting scalar data without interruption by allowing two networks, a LoRa network and a wireless sensor network, with different transmission characteristics to cooperate. It adopts the RT-LoRa protocol for periodic scalar data transmission and uses a WSN-based pipelined transmission method that leverages single-hop message transmission of a LoRa network for image transmission. Thus, it can not only eliminate the control message overhead for time synchronization, slot scheduling, and path establishment for pipelined image transmission in WSNs but also eliminate interferences within WSNs, such as data collisions and data and message collisions, during pipelined image transmission, thereby enabling high reliability and fast transmission.
View Article and Find Full Text PDFJ Imaging
December 2024
School of Innovation, Design and Technology (IDT), Mälardalen University, 72123 Västerås, Sweden.
As the demand for autonomous driving (AD) systems has increased, the enhancement of their safety has become critically important. A fundamental capability of AD systems is object detection and trajectory forecasting of vehicles and pedestrians around the ego-vehicle, which is essential for preventing potential collisions. This study introduces the Deep learning-based Acceleration-aware Trajectory forecasting (DAT) model, a deep learning-based approach for object detection and trajectory forecasting, utilizing raw sensor measurements.
View Article and Find Full Text PDFJ Chem Phys
October 2024
College of Mathematics and Physics, Chengdu University of Technology, Chengdu 610059, China.
The dynamical and conformational properties of the comb polymer with various rigidities of the backbone and arms in steady shear flow are studied by using a hybrid mesoscale simulation approach that combines multiparticle collision dynamics with standard molecular dynamics. First, during the process of the comb polymer undergoing periodic tumbling motion, we find that the rigidity of the arms always promotes the tumbling motion of the comb polymer, but the rigidity of the backbone shifts from hindering to promoting it with increasing the rigidity of the arms. In addition, the comb polymer transitions from vorticity tumbling to gradient tumbling with the increase in shear rate.
View Article and Find Full Text PDFSci Rep
September 2024
Department of Electronics and Communication Engineering, Government College of Technology, Coimbatore, 641013, India.
A Wireless Sensor Network (WSN) is usually made up of a large number of discrete sensor nodes, each of which requires restricted resources, including memory, computing power, and energy. To extend the network lifetime, these limited resources must be used effectively. In WSN, clustering constitutes one of the best methods for optimizing network longevity and energy conservation.
View Article and Find Full Text PDFSensors (Basel)
July 2024
Department of Laser Technologies, FTMC-Center for Physical Sciences and Technology, Savanoriu Ave. 231, LT-02300 Vilnius, Lithuania.
The wide-ranging applications of the Internet of Things (IoT) show that it has the potential to revolutionise industry, improve daily life, and overcome global challenges. This study aims to evaluate the performance scalability of mature industrial wireless sensor networks (IWSNs). A new classification approach for IoT in the industrial sector is proposed based on multiple factors and we introduce the integration of 6LoWPAN (IPv6 over low-power wireless personal area networks), message queuing telemetry transport for sensor networks (MQTT-SN), and ContikiMAC protocols for sensor nodes in an industrial IoT system to improve energy-efficient connectivity.
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